Process Monitoring of Turning and Model Adaptation for Smart Machining Systems

Published

March 1, 2007

Author(s)

Jarred C. Heigel, Robert W. Ivester

Abstract

Smart Machining Systems improve manufacturing efficiency using optimization based on process models. Cutting force models developed from a narrow set of empirical data provide insight into the physical properties of cutting, but the extreme physical phenomena of metal cutting and practical limits on control of environment and material homogeneity, hinder predictability. In order to improve the practicality of model based decision making in an industrial machining environment, this paper introduces a method to adapt parameters of a traditional empirical model in response to on-line measures of process performance to cope with these practical limitations on process predictability. This method enables Smart Machines to self monitor production performance and adapts models and process parameters in response to uncontrollable disturbances, reducing the need for expensive empirical tests.

Proceedings Title

Proceedings of the International Conference on Smart Machining Systems

Conference Dates

March 13-15, 2007

Conference Location

Gaithersburg, MD

Conference Title

International Conference on Smart Machining Systems

Pub Type

Conferences

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Keywords

Adaptation, In-Process Monitoring, Modeling, Smart Machining Systems, Uncertainty

Citation

Heigel, J. and Ivester, R. (2007), Process Monitoring of Turning and Model Adaptation for Smart Machining Systems, Proceedings of the International Conference on Smart Machining Systems, Gaithersburg, MD, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822726 (Accessed June 5, 2023)